Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark this as read-only, idempotent, non-destructive, and open-world, so the bar for behavioral disclosure is lower. The description adds value by stating the source (opendata.cbs.nl), licensing (CC BY 4.0), and access characteristics (no auth, unlimited free access), going beyond what structured fields provide. It does not contradict any annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and information-dense: it states the operation, enumerates output contents, supplies a usage workflow, gives a concrete example, and mentions source/auth constraints. Every sentence earns its place, and the essential purpose is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With a single parameter, full schema coverage, an output schema, and strong annotations, the description is complete for an agent to decide when and how to call this tool. It covers purpose, prerequisite role, example, source, and access model—nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents table_id with an example identifier. The description adds a concrete population-table example and clarifies that the output feeds into table_data queries, but it does not substantially enhance parameter semantics beyond what the schema already provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb and resource: "Get the column schema for a CBS Netherlands statistical table," and lists the exact contents (dimension keys, data types, titles, units, decimal precision). It is distinct from cbs.table.data because it explicitly frames itself as the prerequisite for querying table_data, though it does not differentiate itself from the sibling cbs.table.info, which may overlap in scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context: "Essential before querying table_data" and explains what it reveals (field names, filter values). This gives a strong signal about when to invoke it, but it does not mention when not to use it or explicitly compare it to cbs.table.info or cbs.catalog.search.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.